Ballistic trajectory estimation with angle-only measurements

An iterative least square estimation algorithm is derived and applied to the problem of state estimation of ballistic trajectories with angle only measurements. The application of trajectory a priori knowledge for improving the state estimate is discussed and solved as a constrained estimation problem. A Monte Carlo simulation study was conducted to evaluate these techniques. It was found that the iterative least square filter achieves the Cramer-Rao bound while the extended Kalman filter generally does not.